Inclusion of Red Macroalgae (Asparagopsis taxiformis) in Dairy Cow Diets Modulates Feed Intake, Chewing Activity and Estimated Saliva Secretion

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Milk mid-infrared spectral data as a tool to predict feed intake in lactating Norwegian Red dairy cows

peer-reviewedMid-infrared (MIR) spectroscopy of milk was used to predict dry matter intake (DMI) and net energy intake (NEI) in 160 lactating Norwegian Red dairy cows. A total of 857 observations were used in leave-one-out cross-validation and external validation to develop and validate prediction equations using 5 different models. Predictions were performed using (multiple) linear regression, partial least squares (PLS) regression, or best linear unbiased prediction (BLUP) methods. Linear regression was implemented using just milk yield (MY) or fat, protein, and lactose concentration in milk (Mcont) or using MY together with body weight (BW) as predictors of intake. The PLS and BLUP methods were implemented using just the MIR spectral information or using the MIR together with Mcont, MY, BW, or NEI from concentrate (NEIconc). When using BLUP, the MIR spectral wavelengths were always treated as random effects, whereas Mcont, MY, BW, and NEIconc were considered to be fixed effects. Accuracy of prediction (R) was defined as the correlation between the predicted and observed feed intake test-day records. When using the linear regression method, the greatest R of predicting DMI (0.54) and NEI (0.60) in the external validation was achieved when the model included both MY and BW. When using PLS, the greatest R of predicting DMI (0.54) and NEI (0.65) in the external validation data set was achieved when using both BW and MY as predictors in combination with the MIR spectra. When using BLUP, the greatest R of predicting DMI (0.54) in the external validation was when using MY together with the MIR spectra. The greatest R of predicting NEI (0.65) in the external validation using BLUP was achieved when the model included both BW and MY in combination with the MIR spectra or when the model included both NEIconc and MY in combination with MIR spectra. However, although the linear regression coefficients of actual on predicted values for DMI and NEI were not different from unity when using PLS, they were less than unity for some of the models developed using BLUP. This study shows that MIR spectral data can be used to predict NEI as a measure of feed intake in Norwegian Red dairy cattle and that the accuracy is augmented if additional, often available data are also included in the prediction model

High-digestible silages allow low concentrate supply without affecting milk production or methane emissions

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Effects of the density of extruded pellets on starch digestion kinetics, rumen fermentation, fiber digestibility and enteric methane production in dairy cows

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Cyberlindnera jadinii yeast as a protein source in early- to mid-lactation dairy cow diets: Effects on feed intake, ruminal fermentation, and milk production

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Genetic parameters for cow-specific digestibility predicted by near infrared reflectance spectroscopy

Digestibility traits included in this study were dry matter digestibility (DMD, g/kg), which was calculated based on the indigestible neutral detergent fibre (iNDF, g/kg of dry matter) content in faeces (iNDFf) and in diet (iNDFd), and iNDFf predicted directly from faecal samples by near infrared reflectance spectroscopy (NIRS). The data set was collected at three research herds in Finland and one in Norway including in total 931 records from 328 lactating Nordic Red Cattle and Holstein cows. Observations were associated with different accuracy, due to the differences in sampling protocols used for collecting faecal samples. Heritability estimates varied between different sampling protocols and ranged from 0.14 ± 0.06 to 0.51 ± 0.24 for DMD and from 0.13 ± 0.05 to 0.48 ± 0.18 for iNDFf. Estimated genetic standard deviations were 10.5 g/kg and 6.2 g/kg dry matter for DMD and iNDFf, respectively. Results of our study indicated that recording only the iNDF content in the faeces is sufficient to determine genetic variation in cows’ ability to digest feed. The coefficient of genetic variation for DMD was rather small (1.7%), but could be utilized if it is supported by a positive analysis of benefits over costs.Peer reviewe

Prediction of nitrogen excretion from data on dairy cows fed a wide range of diets compiled in an intercontinental database: a meta-analysis

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Quality of organically grown protein crops in Norway for livestock concentrates – limited N and S supplementation

The aim of organic farming husbandry, is to be entirely based on an organically produced diet. Shortage of organically produced protein crops for production of concentrates supplying the European market, and a contemporary ban on the use of fishmeal for ruminants in the EU has lead to an increased need for organically produced feedstuffs for production of concentrates in Norwegian organic husbandry. Pea is the most common cultivated protein-rich crop in organic agriculture in Norway. For ruminants, peas has a low bypass protein content compared to common protein supplements such as rape meal and soybean meal. Other high-protein crops with complementary properties are therefore needed to meet the demand in feed quality for ruminants, pigs and poultry. Oilseed crops, which are rich in both fat and protein, will become of considerable interest if problems related to their cultivation are solved. Currently, our experience with oilseed crops in organic agriculture is limited. In a four year research project "Organic protein feed and edible oil from oilseed crops" this experience will be extended and the feed quality of organically grown protein crops like rape, turnip rape and camelina will be evaluated. The project will provide knowledge about the rumen degradability of protein, starch and NDF (neutral detergent fibre) and intestine digestibility of protein and starch in organically grown protein-rich crops necessary for the production of concentrates with an optimal feed quality

Effects of three short-term pasture allocation methods on milk production, methane emission and grazing behaviour by dairy cows

Two short-term grazing experiments were conducted with Norwegian Red cows. In Exp 1, 24 cows were randomly assigned to one of the following three pasture allocation methods (PAM): weekly pasture allowance (7RG), grazing 1/7 of 7RG each day (1SG), or grazing as 1SG but had access to grazed part of the paddock within one week (1FG). In Exp 2, 7RG was shortened to 5 days (5RG). We hypothesized that PAM will affect sward quality, quantity, intake and production differently. Pasture chemical composition changed with advancing grazing days but were not different between treatments. Pasture intake, milk yield, and methane emission were not affected by PAM. In Exp 1, 7RG cows spent less time on grazing, whereas in Exp 2, 1FG cows spent longer on grazing than others. Patterns observed in sward quality, and behavioural and physiological adaptations of cows to short-term changes in nutrient supply may explain the observed effects.acceptedVersio